• DocumentCode
    3106185
  • Title

    New Event Detect Based on LDA and Correlation of Subject Terms

  • Author

    Li, Wei ; Huang, Ying

  • Author_Institution
    Sch. of Inf. Eng., Jiangxi Univ. of Sci. & Technol., Ganzhou, China
  • fYear
    2011
  • fDate
    16-18 Aug. 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Nowadays, topic detection and tracking (TDT) has been widely used. As one research tasks for TDT, new event detection can provide prior knowledge to TDT, so it has great theoretical research significance in the field of TDT. Because LDA model cannot automatically identify new events, and the number of LDA topic had been determined by the artificial, or by repeated experiments, it has low efficiency . Here presented a new method, which considering the correlation of subject terms and report time, it can dynamically adaptive updated topics, then detect the new event. This method can adaptive dynamic upload the number of topics, then determinate reasonable theme number. Experiment results demonstrate that this method has some ad-vantages, increased the sensitivity of new events detection.
  • Keywords
    text analysis; LDA; new event detection; report time; subject terms correlation; topic detection; topic tracking; Computational modeling; Correlation; Event detection; Markov processes; Polynomials; Presses; Research and development;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Technology and Applications (iTAP), 2011 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-7253-6
  • Type

    conf

  • DOI
    10.1109/ITAP.2011.6006301
  • Filename
    6006301